| 书目名称 | Recent Advances in Reinforcement Learning | | 编辑 | Leslie Pack Kaelbling | | 视频video | | | 图书封面 |  | | 描述 | .Recent Advances in Reinforcement Learning. addressescurrent research in an exciting area that is gaining a great deal ofpopularity in the Artificial Intelligence and Neural Networkcommunities. .Reinforcement learning has become a primary paradigm of machinelearning. It applies to problems in which an agent (such as a robot, aprocess controller, or an information-retrieval engine) has to learnhow to behave given only information about the success of its currentactions. This book is a collection of important papers that addresstopics including the theoretical foundations of dynamic programmingapproaches, the role of prior knowledge, and methods for improvingperformance of reinforcement-learning techniques. These papers buildon previous work and will form an important resource for students andresearchers in the area. ..Recent Advances in Reinforcement Learning. is an edited volume ofpeer-reviewed original research comprising twelve invitedcontributions by leading researchers. This research work has also beenpublished as a special issue of .Machine Learning. (Volume 22,Numbers 1, 2 and 3). | | 出版日期 | Book 1996 | | 关键词 | Performance; algorithms; artificial intelligence; intelligence; learning; machine learning; programming; pr | | 版次 | 1 | | doi | https://doi.org/10.1007/b102434 | | isbn_softcover | 978-1-4419-5160-1 | | isbn_ebook | 978-0-585-33656-5 | | copyright | Springer Science+Business Media New York 1996 |
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发表于 2025-3-21 17:38:59
